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The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2019, 卷号: 36, 期号: 12, 页码: 1381-1392
作者:  Mu, Bin;  Ren, Juhui;  Yuan, Shijin;  Zhang, Rong-Hua;  Chen, Lei;  Gao, Chuan
Adobe PDF(1429Kb)  |  收藏  |  浏览/下载：197/0  |  提交时间：2020/09/21
optimal precursor  ENSO  gradient-definition-based method  conditional nonlinear optimal perturbation  intermediate coupled model  
Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate model 期刊论文
CLIMATE DYNAMICS, 2019, 页码: 25
作者:  Wei, Yuntao;  Ren, Hong-Li;  Mu, Mu;  Fu, Joshua-Xiouhua
Adobe PDF(10103Kb)  |  收藏  |  浏览/下载：250/0  |  提交时间：2020/03/20
Primary MJO event  CNOP  Nonlinear moisture advection  Nonlinear optimal excitation  
Analysis of typhoon wind hazard in Shenzhen City by Monte-Carlo Simulation 期刊论文
JOURNAL OF OCEANOLOGY AND LIMNOLOGY, 2019, 卷号: 37, 期号: 6, 页码: 1994-2013
作者:  Guo Yunxia;  Hou Yijun;  Qi Peng
Adobe PDF(2079Kb)  |  收藏  |  浏览/下载：153/0  |  提交时间：2020/09/21
typhoon hazard analysis  Monte-Carlo simulation  wind field model  extreme wind speed  
Detecting Change in the Indonesian Seas (vol 6, 257, 2019) 期刊论文
FRONTIERS IN MARINE SCIENCE, 2019, 卷号: 6, 页码: 3
作者:  Sprintall, Janet;  Gordon, Arnold L.;  Wijffels, Susan E.;  Feng, Ming;  Hu, Shijian;  Koch-Larrouy, Ariane;  Phillips, Helen;  Nugroho, Dwiyoga;  Napitu, Asmi;  Pujiana, Kandaga;  Susanto, R. Dwi;  Sloyan, Bernadette;  Pena-Molino, Beatriz;  Yuan, Dongliang;  Riama, Nelly Florida;  Siswanto, Siswanto;  Kuswardani, Anastasia;  Arifin, Zainal;  Wahyudi, A'an J.;  Zhou, Hui;  Nagai, Taira;  Ansong, Joseph K.;  Bourdalle-Badie, Romain;  Chanut, Jerome;  Lyard, Florent;  Arbic, Brian K.;  Ramdhani, Andri;  Setiawan, Agus
Adobe PDF(560Kb)  |  收藏  |  浏览/下载：373/0  |  提交时间：2020/01/03
Indonesian throughflow  observing system  intraseasonal  ENSO  transport variability  planetary waves  
Short-Term Prediction of Bus Passenger Flow Based on a Hybrid Optimized LSTM Network 期刊论文
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2019, 卷号: 8, 期号: 9, 页码: 24
作者:  Han, Yong;  Wang, Cheng;  Ren, Yibin;  Wang, Shukang;  Zheng, Huangcheng;  Chen, Ge
Adobe PDF(9994Kb)  |  收藏  |  浏览/下载：323/0  |  提交时间：2020/01/03
passenger flow  short-term prediction  long short-term memory network  hybrid optimization algorithm  
Effects of Salinity Variability on Recent El Nino Events 期刊论文
ATMOSPHERE, 2019, 卷号: 10, 期号: 8, 页码: 20
作者:  Zhi, Hai;  Zhang, Rong-Hua;  Lin, Pengfei;  Shi, Shiwei
Adobe PDF(10326Kb)  |  收藏  |  浏览/下载：328/0  |  提交时间：2020/01/03
sea surface salinity anomaly  interannual variability  strong and weak El Nino  equatorial Pacific  
Temporal and spatial statistics of travelling eddy variability in the South China Sea 期刊论文
OCEAN DYNAMICS, 2019, 卷号: 69, 期号: 8, 页码: 879-898
作者:  Zhang, Meng;  von Storch, Hans;  Chen, Xueen;  Wang, Dongxiao;  Li, Delei
Adobe PDF(5790Kb)  |  收藏  |  浏览/下载：285/0  |  提交时间：2020/01/03
South China Sea  Statistics of travelling eddies  Variability of characteristics of eddies  Simulation with eddy-permitting model  Internal vs. external variability  
Season-dependent predictability and error growth dynamics for La Nina predictions 期刊论文
CLIMATE DYNAMICS, 2019, 卷号: 53, 期号: 1-2, 页码: 1063-1076
作者:  Hu, Junya;  Duan, Wansuo;  Zhou, Qian
Adobe PDF(3621Kb)  |  收藏  |  浏览/下载：293/0  |  提交时间：2019/08/29
La Nina events  Spring predictability barrier  Initial errors  
A Hybrid Coupled Ocean-Atmosphere Model and Its Simulation of ENSO and Atmospheric Responses 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2019, 卷号: 36, 期号: 6, 页码: 643-657
作者:  Hu, Junya;  Zhang, Rong-Hua;  Gao, Chuan
Adobe PDF(7642Kb)  |  收藏  |  浏览/下载：332/0  |  提交时间：2019/08/28
IOCAS ICM  hybrid coupled model  ENSO simulation  atmospheric response  
Performance of a simple backtracking method for marine oil source searching in a 3D ocean 期刊论文
MARINE POLLUTION BULLETIN, 2019, 卷号: 142, 页码: 321-334
作者:  Chen, Haibo
Adobe PDF(7973Kb)  |  收藏  |  浏览/下载：233/0  |  提交时间：2019/08/29
Backtracking  Marine oil spill  Source searching  Lagrangian particle model